line-bot-mcp-server: MCP server that integrates the LINE Messaging API to connect an AI Agent to the LINE Official Account

by line · MCP Server · ★ 797

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 76/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

linelinebotmcpmcp-server

Quick Facts

Stars797
Forks160
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score76/100
Open Issues10
Last Updated2026-11-05
Created2025-04-04
Platformsmcp, node
Est. Tokens~16k

About line-bot-mcp-server

日本語版 READMEはこちら LINE Bot MCP Server Model Context Protocol (MCP) server implementation that integrates the LINE Messaging API to connect an AI Agent to the LINE Official Account. [!NOTE] This repository is provided as a preview version. While we offer it for experimental purposes, please be aware that it may not include complete functionality or comprehensive support.

Compatible Skills

These tools work well together with line-bot-mcp-server for enhanced workflows:

  • nof1-tracker — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • ai-reviewer — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • postman-mcp-server — semantic(0.46)+same_lang+similar_pop+shared_platform (46%)
  • touchdesigner-mcp — semantic(0.43)+same_lang+similar_pop+shared_platform (45%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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